The best barometer for AI's enterprise value is not replacing the bottom 5% of workers. A better goal is empowering most employees to become 10x more productive. This reframes the AI conversation from a cost-cutting tool to a massive value-creation engine through human-AI partnership.

The common fear of AI eliminating jobs is misguided. In practice, AI automates specific, often administrative, tasks within a role. This allows human workers to offload minutiae and focus on uniquely human skills like relationship building and strategic thinking, ultimately increasing their leverage and value.

Don't view AI through a cost-cutting lens. If AI makes a single software developer 10x more productive—generating $5M in value instead of $500k—the rational business decision is to hire more developers to scale that value creation, not fewer.

In the current market, AI companies see explosive growth through two primary vectors: attaching to the massive AI compute spend or directly replacing human labor. Companies merely using AI to improve an existing product without hitting one of these drivers risk being discounted as they lack a clear, exponential growth narrative.

Coastline Academy frames AI's value around productivity gains, not just expense reduction. Their small engineering team increased output by 80% in one year without new hires by using AI as an augmentation tool. This approach focuses on scaling capabilities rather than simply shrinking teams.

Flexport uses AI agents for tasks that were previously skipped because they were too costly for human employees, like calling warehouses to confirm addresses. This shows that AI's value isn't just in replacing existing work, but in performing new, marginally valuable tasks at a scale that is finally economical.

For companies wondering where to start with AI, target the most labor-intensive, process-driven functions. Customer support is an ideal starting point, as AI can handle repetitive tasks, leading to lower costs, faster response times, and an improved customer experience while freeing up human agents for more complex issues.

While known for external AI applications, Uber's CEO reveals the most significant value from AI comes from internal tools that enhance developer productivity. AI agents for on-call engineering make engineers "superhumans" and more valuable, leading Uber to hire more, not fewer, engineers.

Previously, building 'just a feature' was a flawed strategy. Now, an AI feature that replaces a human role (e.g., a receptionist) can command a high enough price to be a viable company wedge, even before it becomes a full product.